The present invention relates to an approach of updating configurable parameters of a user-defined control program during runtime.
The following discussion of related art is provided to assist the reader in understanding the advantages of the invention, and is not to be construed as an admission that this related art is prior art to this invention.
Industrial automation is used to control machines and processes in manufacturing. An industrial automation installation comprises multiple computerized devices that control industrial processes and devices. The industrial devices generate a large number of variables to be monitored by the industrial automation. The devices of an industrial automation installation must work together in a coordinated way and performing operations. The local control algorithm may also perform local data analytics (on-board analytics).
Industrial controllers and their associated devices are central to the operation of modern industrial automation systems. These controllers interact with field devices on the field floor to control the automated processes relating to such objectives as product manufacture etc. Industrial automation installations can include one or more industrial controllers that monitor and control their processes. The controllers exchange data with field devices using native hardwired I/O or via a plant network such as Ethernet/IP, ControlNet or the like. Industrial controllers receive typically any combination of digital or analog signals from the field devices indicating current states of the devices and their associate processes. Industrial controllers are, for example, programmable logic controllers, (hereinafter referred to as PLC), or programmable controllers.
Industrial controllers store and execute user-defined control programs to effect decision-making in connection with the controlled process based on the received signals by changing the original parameters of the user-defined control program. PLC programs are typically written in a special application on a personal computer, then downloaded by a direct connection cable or over a network to the PLC. Such user-defined control programs can be, according to the IEC 61131-3 (IEC 61131 is an IEC standard for programmable controllers), but are not limited to, a ladder diagram (LD), sequential function charts (SFC), function block programming codes (FBD), structured text (ST), or other such programming structures.
FIG. 1 shows the relationship between an industrial controller and its associated device and the user-defined control program in an industrial automation installation 4. Here, the industrial controller is an engineering station 1 which is used to program a function block as a PLC program 2 (state of the art), which is further deployed for controlling the operation of, for example, a pump process 3. Here, the local control algorithm of the function block performs, for example, local data analytics.
Nowadays, variables from field devices and automation systems are collected and brought (arrow 5) to a network device with a cloud computing infrastructure (hereinafter referred to as cloud 6, FIG. 2). A cloud computing infrastructure can be any infrastructure that allows shared computing services to be accessed and utilized by cloud-capable devices. The cloud computing infrastructure includes one or more communications networks. In some cases, a cloud computing infrastructure can be provided by a cloud provider as a platform-as-a-service (PaaS), and the services can reside and execute in the cloud computing infrastructure as a cloud-based service. Cloud services can generally include, but are not limited to, data storage, data analysis, control applications (e.g., applications that can generate and deliver control instructions to industrial devices based on analysis of near real-time system data or other factors), visualization applications such as cloud-based human-machine interfaces (HMIs), reporting applications, or other such cloud-based applications.
In the cloud 6 of FIG. 2, the data are analyzed with the help of (big) data analytics applications 7 (cloud-based) to identify process improvement potentials and provide insights, for example, optimized parameter(s). The analytics could be automated (e.g., with the help of artificial intelligence and machine learning methods) or semi-automated/manual (where a data scientist or a domain expert analyses the data). The optimized parameters obtained from data analytics have to be implemented (arrow 8) by changing the local control algorithm of the field devices or the automation system.
The control parameters are mainly the process parameters (e.g., certain process set-points, threshold values, parameters of a PID controller, etc.).
Typically, an automation expert takes the results of cloud based analytics, accesses the programming system of the PLC (e.g., STEP7 or TIA portal), modifies the FBs, builds the project and deploys again on the PLC. As this process is manual in nature, it limits the frequency of updating the local control parameters or the control logic. Cloud-based analytics may provide new control parameters several times a day. Due to its manual nature, this is also cost-intensive and error-prone.
It would therefore be desirable and advantageous to provide an improved system and method for updated optimized cloud variables in an automation system based on data analytics in a cloud to obviate prior art shortcomings.